Systems and methods for activities solver development in augmented reality applications

ABSTRACT

Systems and methods for generating an augmented reality interface for generics activities are disclosed. The systems and methods may be directed to creating an augmented reality display for an activity performed on a surface. Given an image of the activity, an activity solver library and associated configuration information for the activity may be selected. The surface of the activity from the image may be rectified, forming a rectified image, from which activity state information may be extracted using the configuration information. The activity state information may be provided to the activity solver library to generate solution information, and elements indicating the solution information may be rendered in a perspective of the original image. By providing the configuration information associated with an activity solver library, an augmented reality interface can be generated for an activity by capturing an image of the activity.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.13/175,252, filed Jul. 1, 2011, the contents of which are incorporatedby reference.

FIELD

This disclosure relates to uses of machine vision and activitiessolvers, and in examples, to augmented reality (AR) activities.

BACKGROUND

Machine vision enables systems and computers to analyze images andextract information useful for controlling an activity. Exemplarysystems may be able to recognize objects in an image in order tounderstand what the objects mean using pre-determined image processingtechniques. Machine vision systems may also enhance images with renderedelements using, for example, augmented reality.

AR may refer to a live direct or indirect view of a physical environmentwhose elements are augmented by computer-generated sensory input.Examples of AR include graphics superimposed on television broadcasts ofsporting events, heads-up displays integrated into car windshields, andhelmet mounted displays worn by pilots.

SUMMARY

This disclosure may disclose, inter alia, systems and methods forgenerating an augmented reality interface for generic activities. Givenan image of an activity performed on a surface and configurationinformation associated with the activity, an augmented reality displayfor the activity may be created. An activity solver library for theactivity can be selected, and rectification of the surface of theactivity, determination of activity state information, and rendering ofelements indicating solution information on the image may be performedutilizing the configuration information.

In one example, a method for generating an augmented reality display fora generic activity is provided. In the method, an image of an activityperformed on a surface is received. The method includes, but is notlimited to, selecting an activity solver library from a plurality ofactivity solvers and configuration information associated with theactivity. The activity solver library is configured to provide solutioninformation for the activity given activity state information. Themethod also includes determining a rectified image of the surface of theactivity based on the configuration information. The rectified image maybe a top-down perspective of the activity performed on the surface. Therectified image may also map each point or a number of points of thesurface within the received image to an expected position within therectified image based on the configuration information. The methodfurther includes processing a fixed set of locations in the rectifiedimage based on the configuration information to determine the activitystate information. The method also includes providing the activity stateinformation to the activity solver library and obtaining solutioninformation from the activity solver library. Based on the solutioninformation, an augmented reality display for the activity may begenerated. The augmented reality display may include rendered elementson the received image in a perspective of the received image.

In another example, a computer-readable medium with instructions storedthereon is provided. The instructions contain instructions executable bya computing device. The instructions may be executable for generating anaugmented reality display for a generic activity. The instructions maybe further executable for receiving an image of an activity performed ona surface. The instructions also may be executable for selecting anactivity solver library from a plurality of activity solvers andconfiguration information associated with the activity. The activitysolver library is configured to provide solution information for theactivity given activity state information. The instructions may befurther executable for determining a rectified image of the surface ofthe activity based on the configuration information. The rectified imagemay be a top-down perspective of the activity performed on the surface.The rectified image may also map each point or a number of points of thesurface within the received image to an expected position within therectified image based on the configuration information. The instructionsalso may be executable for processing a fixed set of locations in therectified image based on the configuration information to determine theactivity state information. The instructions may be further executablefor providing the activity state information to the activity solverlibrary and obtaining solution information from the activity solverlibrary. Based on the solution information, an augmented reality displayfor the activity may be generated. The augmented reality display mayinclude rendered elements on the received image in a perspective of thereceived image.

In another example a system is provided. The system comprises a memoryand a processor coupled to the memory. The system further includesinstructions, executable by the processor, stored in the memory. Theinstructions may be executable by the processor for generating anaugmented reality display for a generic activity. The instructions maybe further executable for receiving an image of an activity performed ona surface. The instructions also may be executable for selecting anactivity solver library from a plurality of activity solvers andconfiguration information associated with the activity. The activitysolver library is configured to provide solution information for theactivity given activity state information. The instructions may befurther executable for determining a rectified image of the surface ofthe activity based on the configuration information. The rectified imagemay be a top-down perspective of the activity performed on the surface.The rectified image may also map each point or a number of points of thesurface within the received image to an expected position within therectified image based on the configuration information. The instructionsalso may be executable for processing a fixed set of locations in therectified image based on the configuration information to determine theactivity state information. The instructions may be further executablefor providing the activity state information to the activity solverlibrary and obtaining solution information from the activity solverlibrary. Based on the solution information, an augmented reality displayfor the activity may be generated. The augmented reality display mayinclude rendered elements on the received image in a perspective of thereceived image.

The foregoing summary is illustrative only and is not intended to be inany way limiting. In addition to the illustrative aspects, embodiments,and features described above, further aspects, embodiments, and featureswill become apparent by reference to the figures and the followingdetailed description.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1A illustrates an example system.

FIG. 1B illustrates an example flow diagram of the system.

FIG. 2 is an example block diagram of a method to generate an augmentedreality display for a generic activity, in accordance with at least someembodiments described herein.

FIG. 3 illustrates an example of a received image and a rectified image.

FIG. 4a illustrates an example of processing a rectified image todetermine activity state information.

FIG. 4b illustrates another example of processing a rectified image todetermine activity state information.

FIG. 4c illustrates another example of processing a rectified image todetermine activity state information.

FIG. 5 illustrates an example of activity state information, updated byan activity solver library and displayed within a rectified image.

FIG. 6 illustrates an example augmented reality interface for anactivity.

FIG. 7 is a functional block diagram illustrating an example computingdevice used in a computing system that is arranged in accordance with atleast some embodiments described herein.

FIG. 8 is a schematic illustrating a conceptual partial view of anexample computer program product that includes a computer program forexecuting a computer process on a computing device, arranged accordingto at least some embodiments presented herein.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying figures, which form a part hereof. In the figures, similarsymbols typically identify similar components, unless context dictatesotherwise. The illustrative embodiments described in the detaileddescription, figures, and claims are not meant to be limiting. Otherembodiments may be utilized, and other changes may be made, withoutdeparting from the scope of the subject matter presented herein. It willbe readily understood that the aspects of the present disclosure, asgenerally described herein, and illustrated in the figures, can bearranged, substituted, combined, separated, and designed in a widevariety of different configurations, all of which are explicitlycontemplated herein.

This disclosure may disclose, inter alia, systems and methods forgenerating an augmented reality interface for generic activities. Animage of an activity performed on a surface may be received. An activitysolver library corresponding to the activity and configurationinformation associated with the activity may be selected. The activitysolver library may be selected from among a plurality of activitysolvers and can be configured to provide solution information for theactivity given activity state information.

In one example, based on the received image of the surface of theactivity and the configuration information, a rectified image of thesurface is determined. The rectified image may be a top-down perspectiveof the activity performed on the surface. Additionally, each point ofthe surface within the received image may be mapped to an expectedposition within the rectified image. The configuration information maybe utilized to process a fixed set of locations within the rectifiedimage to determine activity state information. The activity stateinformation may be provided to the activity solver library to obtainsolution information from the activity solver library. Further, based onthe solution information, rendered elements in a perspective of thereceived image may be rendered on the received image, generating anaugmented reality display for the activity.

In another example, the configuration information associated with theactivity may describe the surface of the activity. For example, theconfiguration information may describe the surface of the activity as arectangular grid including a number or rows and columns. Theconfiguration information may also describe a relationship of relativefeatures on the surface. The rectified image may be determined based onthe configuration information. For example, four corners of the surfaceof the activity within the received image may be mapped to four cornersof the rectified image. In one example, a homography matrix may bedetermined mapping points within the received image to points within therectified image. Moreover, an inverse of the homography matrix may beused to render solution information from the rectified image in theperspective of the received image on the received image.

In another example, the configuration information associated with theactivity may include information identifying the fixed set of locationswithin the rectified image to be processed, as well as information usedto classify activity state information for the fixed set of locations.

In an additional example, activity state information may be provided tothe selected activity solver library as a first array of integersindicating information about the fixed set of locations. Positionswithin the first array of integers may correspond to activity stateinformation for locations within the processed fixed set of locations ofthe rectified image. Also, the activity solver library may providesolution information as a second array of integers. In some examples,differences between the first array of integers and second array ofintegers may be provided as rendered elements in the rectified image.

Referring now to the figures, FIG. 1A illustrates an example system 100.The system 100 includes a processor 102, a memory 104 storing arectifier 106, a classifier 108, and a renderer 110. Additionally, thesystem 100 may include or access a configuration information database112 and activity solver library database 114.

The processor 102 may be any type of processor, such as amicroprocessor, digital signal processor (DSP), multicore processor,etc., coupled to the memory 104. The memory 104 may be any type ofmemory, such as volatile memory like random access memory (RAM), dynamicrandom access memory (DRAM), static random access memory (SRAM), ornon-volatile memory like read-only memory (ROM), flash memory, magneticor optical disks, or compact-disc read-only memory (CD-ROM), among otherdevices used to store data or programs on a temporary or permanentbasis.

The rectifier 106, classifier 108, and renderer 110 may be computermodules. The modules may be a segment, or portion of program code, whichincludes one or more instructions executable by the processor 102 forimplementing specific logical functions or steps.

In one example, the system 100 may receive as input a received image116, and generate an augmented reality display 118, as described in FIG.1B, for example.

FIG. 1B illustrates an example flow diagram of the system 100. Thesystem 100 may receive as input the received image 116 of an activityconfigured to be performed on a surface. The augmented reality display118 for the activity may be output by the system 100. The system 100 mayalso select an activity solver library 120 and configuration information122 to generate the augmented reality display 118 for the activity.

In one example, the rectifier 106 may be configured to locate thesurface of the activity in the image 116 using the configurationinformation 106. The rectifier 106 may output a rectified image 124 ofthe surface such that each point on the surface is mapped to a positionon the rectified image 124, or such that a number of points (one ormore, a substantial number, corner points, etc.) are mapped to aposition on the rectified image 124. For example, the activity may be agame of Checkers, and the rectifier 106 may identify a rectangular gridin the image 116 as a checkerboard. The rectifier 106 may rectify theimage 116 such that four corners of the checkerboard correspond to fourcorners of the rectified image 124. In some examples, the activity maybe played on multiple surfaces and the rectifier 106 may output one ormore rectified images of the surfaces.

In one example, the classifier 108 may be configured to receive therectified image 124 and to extract activity state information 126. Thismay be accomplished by examining a fixed set of locations in therectified image 124. The configuration information 122 may provideinformation identifying the fixed set of locations within the rectifiedimage 124. Additionally, the configuration information 122 may provideinformation identifying how to determine activity state information 126at the fixed set of locations within the rectified image 124. In oneexample, the activity state information 126 may be an array of integers.A position in the array of integers may indicate activity stateinformation 126 for a location within the fixed set of locations.Similarly, the activity state information 126 may take the form of anylogical data structure for maintaining information regarding the stateof the activity.

The activity state information 126 may be provided to the activitysolver library 120 in one example. The activity solver library 120 maybe selected from among a plurality of activity solver libraries 128 a,128 b, and 128 c. The plurality of activity solver libraries 128 a, 128b, and 128 c may be associated with a variety of different activities.Additionally, the plurality of activity solver libraries 128 a, 128 b,and 128 c may be existing, open-source, implementations of librariesthat can perform, solve, or provide advice associated with theactivities. The configuration information 122 may provide information toconvert the activity state information 126 to a native representation ofthe activity solver library 120. For example, the configurationinformation 122 may include a function used to convert activity stateinformation 126 in the form of an array of integers to a data structureusable by the activity solver library 120.

In another example, the activity solver library 120 may output solutioninformation 130. The solution information 130 may be one or anycombination of updated activity state information, a next moveassociated with the activity or multiple next moves, advice regardingthe activity state information 126, among other possibilities. In oneexample, the configuration information 122 may provide information usedto convert information output by the activity solver library 120 to thesolution information 130. In some examples, the solution information 130may be in the same form as the activity state information 126. Forexample, one or more of the activity state information 126 and solutioninformation 130 may be an array of integers.

In one example, the solution information 130 may be provided to therenderer 110. The renderer 110 may output the solution information 130as rendered elements on the rectified image 124. The rendered elementson the rectified image 124 may be viewable on a conventional display(e.g., liquid crystal display (LCD), light-emitting diode (LED) display,etc.) of a computing device or user interface device. Additionally, therenderer 110 may enhance the received image 116 with the renderedelements in the perspective of the image 116, producing an augmentedreality interface. In some examples, the rendered elements may overlaythe image 116 or overlay a live video stream of the activity.

In one embodiment, the system 100 may be a toolkit for generating anaugmented reality display 118 for a generic activity performed on asurface. The toolkit may include the rectifier 106, classifier 108,renderer 110, and a wrapping function used to call the game solvinglibrary 120 for the activity. By selecting the game solving library 120and configuration information 122 for the activity, an augmented realitydisplay 118 may be generated using the toolkit without requiringknowledge of machine vision or image processing techniques. Theconfiguration information 122 may provide information used to identifythe surface of the activity from the image 116 and generate therectified image 124. Similarly, the configuration information 122 mayprovide information to infer the activity state information 126 from atop-down view of the surface. The toolkit described may aim to supportno activity in particular, but allow potentially any activity performedon a surface to be supported.

FIG. 2 is an example block diagram of a method 200 to generate anaugmented reality display for a generic activity, in accordance with atleast some embodiments described herein. The method 200 shown in FIG. 2presents an embodiment of a method that may, for example, be used by thesystem 100 of FIG. 1. Method 200 may include one or more operations,functions, or actions as illustrated by one or more of blocks 201-211.Although the blocks are illustrated in a sequential order, these blocksmay also be performed in parallel, and/or in a different order thanthose described herein. Also, the various blocks may be combined intofewer blocks, divided into additional blocks, and/or removed from themethod, based upon the desired implementation of the method.

In addition, for the method 200 and other processes and methodsdisclosed herein, the flowchart shows functionality and operation of onepossible implementation of present embodiments. In this regard, eachblock may represent a module, a segment, or a portion of program code,which includes one or more instructions executable by a processor forimplementing specific logical functions or steps in the process. Theprogram code may be stored on any type of computer readable medium, forexample, such as a storage device including a disk or hard drive. Thecomputer readable medium may include non-transitory computer readablemedium, for example, such as computer-readable media that stores datafor short periods of time like register memory, processor cache andrandom access memory (RAM). The computer readable medium may alsoinclude non-transitory media, such as secondary or persistent long termstorage, like read only memory (ROM), optical or magnetic disks,compact-disc read only memory (CD-ROM), for example. The computerreadable media may also be any other volatile or non-volatile storagesystems. The computer readable medium may be considered a computerreadable storage medium, for example, or a tangible storage device.

In addition, for the method 200 and other processes and methodsdisclosed herein, each block in FIG. 2 may represent circuitry that iswired to perform the specific logical functions in the process.

Initially, at block 201, the method 200 includes receiving an image ofan activity configured to be performed on a surface. In one example, theimage 102 may be received from a user interface. The image 102 may becaptured, for example, through any type of imaging device. The image 102may be received from a built-in camera of a mobile device.Alternatively, the image 102 may be captured as frames of a video streamor screenshots of a virtual game. In another example, the image 102 maybe captured using a computing device with a camera. The camera may avideo camera, or webcam, for example. Additionally, the image may becaptured by a robot, a toy, a gaming counsel with a camera, among otherpossible computing devices with a camera.

The image may be received at a server, a user-client device, or ageneral computing device. In one example, the image may be captured by aclient device and sent to a server for processing.

At block 203, the method 200 includes selecting from among a pluralityof activity solvers, an activity solver library corresponding to theactivity and configuration information associated with the activity. Theactivity solver library may be configured to provide solutioninformation for the activity given activity state information. Theactivity solver library may be selected based on the current activitycaptured in the image. Also, the configuration information may beprovided as information for generating an augmented reality display forthe activity of the image. In one example, contingent on theavailability of activity solver libraries associated with activities,the method 200 may be applicable to any generic activity performed on asurface. An activity solver library and associated configurationinformation may be provided in a database for association with anyactivity solver library. The activity solver library and configurationinformation associated with an activity may be selected from thedatabase, using a processor of a computing device.

At the block 205, the method 200 includes determining a rectified imageof the surface of the activity based on the received image and theconfiguration information. The method 200 may be flexible to determine arectified image of the surface of a wide range of activities. Therectified image may be a top-down perspective of the activity performedon the surface. Additionally, each point of the surface within thereceived image may map to an expected position within the rectifiedimage. Alternatively, some points, a substantial number of points, orlandmark points (e.g., corners, center, etc.) of the surface within therectified image may map to positions in the rectified image.

In one example, a rectified image of the surface of the activity isdetermined using quadrilateral rectification. Perspective-deformedelements in the received image may be located to produce an expectedtop-down perspective of the elements. Edges of a potential elementforming a polygon may be recognized in the received image. For example,edges of a quadrilateral forming a convex polygon may be identified. Thequadrilateral may be rectified, or righted and straightened to alignwith the rectified image, such that each edge of the quadrilateral isparallel to an edge of the rectified image. In one embodiment, theconfiguration information may indicate the surface of an activity is arectangular surface. A rectified image of the rectangular surface maythen be output.

In another example, a rectified image of the surface of the activity isdetermined using feature-based matching. The configuration informationmay include a set of training images of the surface of the activity. Themethod 200 may include detecting a relative arrangement of featureswithin the received image to construct a mapping between the receivedimage and the rectified image. A robust object detector or algorithm(e.g., scale-invariant feature transform (SIFT), an image recognitionengine, speeded up robust features (SURF), etc.) may be trained on theset of training images of the surface. If the surface is detected in thereceived image, the relative arrangement of the features of the surfacecan be used to construct a mapping from the received image to therectified image.

At block 207, the method 200 includes processing a fixed set oflocations in the rectified image based on the configuration informationto determine the activity state information. In one example, the fixedset of locations is determined based on the configuration informationassociated with the activity. Various techniques may be used forexamining and classifying information of the rectified image todetermine the activity state information. The configuration informationmay indicate the method or technique to be used to determine theactivity state information and include any parameters necessary for themethod or technique.

In one example, color matching may be used to determine the activitystate information. Processing the fixed set of locations may includedetermining regions of colors within the fixed set of locations. Theconfiguration information may include information identifying colorsthat may occur within the fixed set of locations and information used toconvert the determined regions of color to activity state informationfor the fixed set of locations. The configuration information mayspecify which colors to look for, or at least how many different colorsmay occur. For example, in an activity performed with black and whitepieces on a brown surface, the configuration information may include thethree colors of black, white, and brown and their associatedrepresentations. Processing the fixed set of locations may includedetermining if a location is black, white, or brown. This informationmay then be translated to an integer, or other data structure, as aportion of the activity state information. A black color found withinthe location may indicate the presence of a black piece, and an integer,(1), for example, may be determined representing the black piece. Anaverage pixel value within the location may be determined and comparedwith the possible colors to determine the closest match, and most likelyclassification of the location.

In another example, optical character recognition (OCR) may be used todetermine the activity state information. Processing the fixed set oflocations may include determining characters within the fixed set oflocations using OCR. The configuration information may comprise a listof characters to be recognized and information used to convert thedetermined characters to activity state information for the fixed set oflocations. OCR may return the most likely characters within the fixedset of locations by comparing information within the rectified image tothe list of characters. Additionally, a character within a location mayconfigured to an integer value to be included within the activity stateinformation. The configuration information may include information toconvert the character to the integer. A lookup table may be used forexample to convert the list of characters to integers.

In another example, feature matching may be used to determine theactivity state information. Feature matching may be used, for example,in activities with pieces, tokens, or objects. A set of example imagesof pieces, tokens, or objects to be matched may be provided by theconfiguration information. Feature matching may then be used todetermine the most likely pieces, tokens, or objects, if any, associatedwith the fixed set of locations of the rectified image. A robust objectdetector or algorithm (e.g., scale-invariant feature transform (SIFT),an image recognition engine, speeded up robust features (SURF), etc.)may be trained on the set of example images and used for the featurematching. Configuration information may provide information necessary toconvert the matched pieces, tokens, or objects to activity stateinformation.

In some examples, a combination of techniques or methods may be used todetermine activity state information for an activity. One or more of theabove methods, or additional methods may be employed to determine theactivity state information by processing the rectified image.

In one example, the activity may be a game of Go. The activity may beperformed on a 19-by-19 grid of lines forming 361 evenly spacedintersections. Players of Go may place black or white stones onintersections of the lines to perform the activity. The configurationinformation may provide information indicating to determine an averagepixel color value at intersections of the grid lines. The average pixelcolor value may then be compared to a set of colors provided by theconfiguration information. Black stones, white stones, and blank spacesmay be classified as respective values of 0, 1, or 2. The activity stateinformation may be an array of 361 integers, where each of the 361intersections of the grid lines may be represented by an integer withinthe array.

In another example, the activity may be a game of Sudoku. Theconfiguration information may indicate the use of OCR to determinecharacters of a 9-by-9 table of 81 positions. The configurationinformation may indicate as a list of characters the digits 1 through 9.Processing the rectified image may produce an array of 81 integerscorresponding to digits for each of the positions. Blank positions maybe associated with the integer zero.

At block 209, the method 200 includes providing the activity stateinformation to the activity solver library and obtaining solutioninformation from the activity solver library. The activity solverlibrary may perform, solve, or provide advice for the activity assolution information. The configuration information may includeinformation to convert the activity state information as an array ofintegers to information in a form of input acceptable by the activitysolver library.

The activity solver library may process the activity state informationand provide or output an updated activity state as solution information.The solution information may, in some examples, be converted back to anarray of integers as activity state information and provided to arenderer module. In one example, the solution information may includeother information used to create activity-specific rendered elements.The configuration information may provide information to process theinformation output by the activity solver library into a form ofsolution information suitable for creating rendered elements on therectified image of the activity.

In one example, a confidence level of the activity state informationassociated with an individual location within the fixed set of locationsmay be determined. Solution information obtained from the activitysolver library may include information identifying an illegal activitystate. A confidence level of the activity state information associatedwith the individual location may be used to correct the activity stateinformation associated with the individual location. For example, theactivity may be a game of Sudoku, and additional heuristics such as thevalidity of the activity state information can be used to enhance theaccuracy of the activity state information. If the activity stateinformation wrongly identified two 8's in the same row (an illegalstate), the 8 with the least confidence could be changed to be a 3. Inanother example, the configuration information may include informationidentifying legal and illegal states such that illegal states could beidentified prior to providing activity state information to the activitysolver library.

At block 211, the method 200 includes based on the solution information,generating an augmented reality display for the activity. The augmentedreality display may include rendered elements on the received image in aperspective of the received image. Rendered elements associated with thesolution information may be created on the rectified image of theactivity. In one example, activity state information is provided to theactivity solver library as a first array of integers. The activitysolver outputs solution information associated with the first array ofintegers. The solution information is converted to a second array ofintegers using the configuration information. A difference between thefirst array of integers and the second array of integers is determined,and the difference is provided as rendered elements in the rectifiedimage.

In one example, the configuration information may include informationdescribing how to render the solution information. Solution informationmay be in the form of activity state information, and activity stateinformation may be rendered according to the method or technique used toclassify the activity state information. For example, for color matchingscenarios, the renderer may provide a blob of an appropriate color at alocation in the rectified image. Similarly, for OCR scenarios, therendered may print an appropriate character or group of characters atthe location. For feature matching scenarios, an appropriate exampletraining image may be drawn at the location.

In another example, the method 200 may further include determining ahomography matrix mapping points within the received image to pointswithin the rectified image. Any two images of a planar surface in spacemay be related by a homography, where the homography is a projectivelinear transformation. A homography matrix may include informationdescribing camera motion, (i.e., rotation and/or translation) betweencamera positions used to create the two images. Given rendered elementsin the rectified image, an inverse of the homography matrix may be usedto render the rendered elements in the rectified image in theperspective of the received image. The rendered elements may be renderedin a correct perspective and appear to have been part of the originalscene, or received image, creating an augmented reality.

FIG. 3 illustrates an example of a received image 301 and a rectifiedimage 303. In one example, the rectified image 303 may be determinedbased on the received image 301 and associated configurationinformation. The configuration information may indicate an activity thatis performed on a surface 305 including two intersecting perpendicularlines forming a 2-by-2 grid of four cells. The configuration informationmay also include information indicating the presence of a first feature307 and a second feature 309 on the surface 305.

In one example, the rectified image 303 may be determined using acombination of quadrilateral rectification and feature matching.Quadrilateral rectification may be used to determine the surface 305 andfeature matching may use a set of training images to identify the firstfeature 307 and second feature 309. An algorithm may be used to identifylines forming perspective-deformed cells within the received image 301.A relative arrangement of the first feature 307 and second feature 309may also be used to determine a proper orientation of the surface 305 inthe rectified image 303. For example, the configuration information mayindicate the presence of the first feature 307 in the upper right handcorner and the second feature 309 in the lower left hand corner.

The rectified image 303 may map points on the surface 305 in thereceived image 301 to expected positions within the rectified 303. InFIG. 3, dotted lines represent the relationship between points on thesurface 305 in the received image 301 and points in the rectified image303. Additionally, in FIG. 3, four corners of the surface 305 in thereceived image 301 map to four corners of the rectified image 303. Insome examples, a homography matrix associated with the relationshipbetween the received image 301 and rectified image 303 may also bedetermined.

FIG. 4a illustrates an example of processing a rectified image 401 a todetermine activity state information. Configuration information mayindicate the use of color matching to determine activity stateinformation. The configuration information may also indicate a fixed setof locations to process. For example, the rectified image 401 a may be asquare surface including 16 evenly spaced cells of a 4-by-4 grid.Processing a first location 403 a may indicate an average pixel colorvalue associated with a first color. Activity state information mayinclude information indicating the presence of an activity piece withthe first color in the first location 403 a. Processing a secondlocation 405 a, an average pixel color value associated with a secondcolor may be determined. The second color may be closest to a colordefined in the configuration information that is associated with thesurface. The second location 405 a may be determined to be blank orempty, and the activity state information may indicate the empty space.According to the same manner, additional locations within the fixed setof locations may be processed to determine the activity stateinformation for the activity.

FIG. 4b illustrates another example of processing a rectified image 401b to determine activity state information. Configuration information mayindicate the use of OCR to determine activity state information. Thesurface of an activity may include 16 evenly spaced cells of a 4-by-4grid. Although the surface is illustrated as a grid of 16 evenly spacedcells, the surface may be any shape and potentially include no cells, orany number of cells. Cells within the rectified image 401 b may possiblycontain digits or letters. Processing a first location 403 b, OCR maydetermine the letters “dog”. Although the characters of location 403 bare arranged left-to-right forming the word “dog”, in some examples,characters within a location of a surface may be arranged in multiplerows and/or separated by any amount of blank space. Processing a secondlocation 405 b, OCR may determine the digit “4”. Additionally,processing some locations may not determine any characters for alocation, and a location may be determined to be blank. Theconfiguration information may indicate how to convert the determinedcharacters to activity state information for the rectified image 401 b.

FIG. 4c illustrates another example of processing a rectified image 401c to determine activity state information. Configuration information mayindicate the use of feature matching to determine activity stateinformation. A first location 403 c in the upper left hand corner of therectified image 401 c may be processed. Similarly, a second location 405c may be processed. Features within the first location 403 c and secondlocation 405 c may be identified using a set of training images 407 c ofactivity pieces, tokens, or objects. For example, processing the firstlocation 403 c may result in the identification of a first feature, animage of a dog, from the set of training images 407 c. Also, processingthe second location 405 c may result in the identification of the samefirst feature, as well identification of a second feature, an image of adie with a face including 3 dots (i.e., a traditional cubic die with aresting attitude representing the number 3). The configurationinformation may indicate how to convert the identified features toactivity state information for the rectified image 401 c.

As illustrated in FIG. 4c , locations of the fixed set of locations mayoverlap. In other examples, locations of the fixed set of locations mayeach cover exclusive portions of the rectified image 401 c, such thatlocations of the fixed set of locations do not overlap. In one example,every point within the rectified image 401 c may be processed.Alternatively, in other examples, the points covered by the fixed set oflocations collectively may not cover the entire rectified image 401 c.In another example, as illustrated in FIG. 4c , the second location 405c may be the entire rectified image 401 c.

In some examples, locations of the fixed set of locations may beprocessed in a logical manner, starting with an initial location in theupper left hand corner of a rectified image, proceeding left-to-rightacross the image, and top-to-bottom to process other locations.Alternatively, locations of the fixed set of locations may be processedin any random or logical fashion.

FIG. 5 illustrates an example of activity state information 501, updatedby an activity solver library 503 and displayed within a rectified image505. The activity solver library 503 may output solution information 507in the same form as the activity state information 501. In one example,an activity may be a game of Tic-Tac-Toe. Activity state information 501may be determined using feature matching or OCR. Three classes ofinformation may exist for a 3-by-3 grid of evenly spaced positionswithin the rectified image 505. For example, crosses or “X's” may beassociated with the integer zero, “O's” may be associated with theinteger one, and empty or blank spaces may be associated with theinteger two. Activity state information may be processed left-to-right,top-to-bottom to determine an array of nine integers representingactivity state information.

In one example, activity state information 501 may be an array of nineintegers classifying the rectified image 505. The activity stateinformation may be provided to the activity solver library 503, andsolution information 507 may be obtained. The solution information 507may be updated activity state information illustrating a potential nextaction or solution for the game. A difference between the solution 507information and activity state information 501 may be determined. In theexample of FIG. 5, the seventh integer in the solution information 507,a zero, differs from the seventh integer of the activity stateinformation 501, a two. As a result, the class of information associatedwith the integer zero may be provided in the rectified image 505 at thelocation associated with the seventh integer. The seventh integer isassociated with the bottom left position. Therefore, a cross is renderedat the bottom left position of the rectified image 505.

FIG. 6 illustrates an example augmented reality interface for anactivity. In the example, the activity is a game of Checkers implementedusing an open source Checkers solver library. An input image 601 of theactivity may be provided to a rectifier. The rectifier may usequadrilateral rectification to produce a rectified image 603 and ahomography matrix mapping pixels of the received image 601 to pixels ofthe rectified image 603. Configuration information may indicate use ofcolor matching to examine 16 evenly spaced positions at the center ofthe 16 positions of the rectified image 603. Activity state informationmay be determined from the rectified image 603 based on relationships ofaverage pixel color values of the 16 positions compared to four colorsspecified by the configuration information. The four colors may be blackand white, for the colors of a surface of the game, and any two othercolors associated with the checkers used to play the game. The activitystate information may be provided to an activity solver library, theopen source Checkers solver library, to obtain solution information. Thesolution information may be rendered on the rectified image, creatingthe updated rectified image 605. Additionally, the solution informationmay be rendered in a perspective of the received image, creating anaugmented reality display 607 using an inverse of the homography matrix.The rendered elements of the augmented reality display 607 may berendered multiple frames per second, in real-time. As shown in theexample augmented reality display 607, elements such as an arrow showinga next move may be provided over the received image 601, for example.

In one example, a user may perform a turn and subsequently capture animage of the game producing the received image 601. The activity solverlibrary may determine a modified game state of the game representing acomputer's next move against the user. A user may then mimic the moveindicated by the rendered elements in the augmented reality display 607.The user may repeat the process to continue playing Checkers against thecomputer. In another example, a first user playing against a second usermay capture an image of the game at the first user's turn. The activitysolver library may indicate a next move or advice for the first user.

Additional embodiments of generating augmented reality interfaces foractivities are also contemplated. In one embodiment, the activity may beinformation rendered on a document. Solution information provided by anactivity solver library may include information indicating explanationof the information rendered on the document. The information may be oneor more equations, one or more questions, or other types of informationrequiring an explanation.

In another embodiment, a hand-held gaming device or mobile device maycapture an image of an activity in order to determine a solution oradvice for the activity. A sample of the activities, not intended to belimiting, may include Checkers, Connect-4, Go, Ludo, Risk, Sudoku,Crossword puzzles, among others. In another embodiment, an augmentedreality interface may be created for activities performed with playingcards or dice. The surface of the activity may be a table or othersurface on which the activity is performed. The surface of the activityneed not be a game board or other particular surface on which the gameis performed. A surface may be interpreted and expanded to include anarea around recognized activity pieces, objects, or tokens of theactivity. The surface may further include any surface upon which anactivity can be performed, for example.

In another embodiment, an augmented reality interface may be created foractivities of game shows or tournaments. For example, monitoring andupdating of a game state in chess, Go, or poker tournaments may bepossible. Rendering of possible next moves or commentator adviceregarding the tournament or game show may be performed to create anaugmented reality display for the activity.

In another embodiment, robots with cameras may be able to performactivities by capturing an image of the activity and extracting activitystate information for the activity. The robots may be able to perform anext action associated with the activities based on the extractedactivity state information. For example, a robot may be able to play aphysical game of Checkers on a surface.

FIG. 7 is a functional block diagram illustrating an example computingdevice 700 used in a computing system that is arranged in accordancewith at least some embodiments described herein. The computing devicemay be a personal computer, mobile device, cellular phone,touch-sensitive wristwatch, tablet computer, video game system, orglobal positioning system, and may be implemented to generate anaugmented reality interface as described in FIGS. 1-6. In a very basicconfiguration 702, computing device 700 may typically include one ormore processors 710 and system memory 720. A memory bus 730 can be usedfor communicating between the processor 710 and the system memory 720.Depending on the desired configuration, processor 710 can be of any typeincluding but not limited to a microprocessor (μP), a microcontroller(μC), a digital signal processor (DSP), or any combination thereof. Amemory controller 715 can also be used with the processor 710, or insome implementations, the memory controller 715 can be an internal partof the processor 710.

Depending on the desired configuration, the system memory 720 can be ofany type including but not limited to volatile memory (such as RAM),non-volatile memory (such as ROM, flash memory, etc.) or any combinationthereof. System memory 720 may include one or more applications 722, andprogram data 724. Application 722 may include an image display algorithm723 that is arranged to provide inputs to the electronic circuits, inaccordance with the present disclosure. Program data 724 may includecontent information 725 that could be directed to any number of types ofdata. In some example embodiments, application 722 can be arranged tooperate with program data 724 on an operating system.

Computing device 700 can have additional features or functionality, andadditional interfaces to facilitate communications between the basicconfiguration 702 and any devices and interfaces. For example, datastorage devices 740 can be provided including removable storage devices742, non-removable storage devices 744, or a combination thereof.Examples of removable storage and non-removable storage devices includemagnetic disk devices such as flexible disk drives and hard-disk drives(HDD), optical disk drives such as compact disk (CD) drives or digitalversatile disk (DVD) drives, solid state drives (SSD), and tape drivesto name a few. Computer storage media can include volatile andnonvolatile, non-transitory, removable and non-removable mediaimplemented in any method or technology for storage of information, suchas computer readable instructions, data structures, program modules, orother data.

System memory 720 and storage devices 740 are examples of computerstorage media. Computer storage media includes, but is not limited to,RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM,digital versatile disks (DVD) or other optical storage, magneticcassettes, magnetic tape, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to store thedesired information and which can be accessed by computing device 700.Any such computer storage media can be part of device 700.

Computing device 700 can also include output interfaces 750 that mayinclude a graphics processing unit 752, which can be configured tocommunicate to various external devices such as display devices 760 orspeakers via one or more A/V ports or a communication interface 770. Thecommunication interface 770 may include a network controller 772, whichcan be arranged to facilitate communications with one or more othercomputing devices 780 over a network communication via one or morecommunication ports 774. The communication connection is one example ofa communication media. Communication media may be embodied by computerreadable instructions, data structures, program modules, or other datain a modulated data signal, such as a carrier wave or other transportmechanism, and includes any information delivery media. A modulated datasignal can be a signal that has one or more of its characteristics setor changed in such a manner as to encode information in the signal. Byway of example, and not limitation, communication media can includewired media such as a wired network or direct-wired connection, andwireless media such as acoustic, radio frequency (RF), infrared (IR) andother wireless media.

Computing device 700 can be implemented as a portion of a small-formfactor portable (or mobile) electronic device such as a cell phone, apersonal data assistant (PDA), a personal media player device, awireless web-watch device, a personal headset device, an applicationspecific device, or a hybrid device that include any of the abovefunctions. Computing device 700 can also be implemented as a personalcomputer including both laptop computer and non-laptop computerconfigurations.

In some embodiments, the disclosed methods may be implemented ascomputer program instructions encoded on a non-transitorycomputer-readable storage media in a machine-readable format, or onother non-transitory media or articles of manufacture. FIG. 8 is aschematic illustrating a conceptual partial view of an example computerprogram product 800 that includes a computer program for executing acomputer process on a computing device, arranged according to at leastsome embodiments presented herein. In one embodiment, the examplecomputer program product 800 is provided using a signal bearing medium801. The signal bearing medium 801 may include one or more programminginstructions 802 that, when executed by one or more processors mayprovide functionality or portions of the functionality described abovewith respect to FIGS. 1-7. Thus, for example, referring to theembodiments shown in FIG. 2, one or more features of blocks 201-211 maybe undertaken by one or more instructions associated with the signalbearing medium 801.

In some examples, the signal bearing medium 801 may encompass acomputer-readable medium 803, such as, but not limited to, a hard diskdrive, a Compact Disc (CD), a Digital Video Disk (DVD), a digital tape,memory, etc. In some implementations, the signal bearing medium 801 mayencompass a computer recordable medium 804, such as, but not limited to,memory, read/write (R/W) CDs, R/W DVDs, etc. In some implementations,the signal bearing medium 801 may encompass a communications medium 805,such as, but not limited to, a digital and/or an analog communicationmedium (e.g., a fiber optic cable, a waveguide, a wired communicationslink, a wireless communication link, etc.). Thus, for example, thesignal bearing medium 801 may be conveyed by a wireless form of thecommunications medium 805 (e.g., a wireless communications mediumconforming with the IEEE 802.11 standard or other transmissionprotocol).

The one or more programming instructions 802 may be, for example,computer executable and/or logic implemented instructions. In someexamples, a computing device such as the computing device 700 of FIG. 7may be configured to provide various operations, functions, or actionsin response to the programming instructions 802 conveyed to thecomputing device 700 by one or more of the computer readable medium 803,the computer recordable medium 804, and/or the communications medium805.

It should be understood that arrangements described herein are forpurposes of example only. As such, those skilled in the art willappreciate that other arrangements and other elements (e.g. machines,interfaces, functions, orders, and groupings of functions, etc.) can beused instead, and some elements may be omitted altogether according tothe desired results. Further, many of the elements that are describedare functional entities that may be implemented as discrete ordistributed components or in conjunction with other components, in anysuitable combination and location.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopebeing indicated by the following claims, along with the full scope ofequivalents to which such claims are entitled. It is also to beunderstood that the terminology used herein is for the purpose ofdescribing particular embodiments only, and is not intended to belimiting.

What is claimed is:
 1. A computer-implemented method comprising:receiving an image; determining an activity being performed in thereceived image, wherein the activity is configured to be performed on asurface; selecting (i) a particular activity solver, from a set ofactivity solvers stored in memory, that provides solution data for theactivity being performed in the received image and (ii) configurationdata associated with the activity being performed in the received image;based on the configuration data associated with the activity beingperformed in the received image, (i) generating a rectified image of thesurface of the activity performed in the received image, and (ii)determining an activity state of the activity being performed in thereceived image; wherein determining an activity state of the activitybeing performed in the received image is based on the rectified image inaddition to the configuration data associated with the activity beingperformed in the received image; providing data indicating the activitystate to the particular activity solver, selected from the set ofactivity solvers, that provides solution data for the activity beingperformed in the received image; in response to providing dataindicating the activity state to the particular activity solver,obtaining solution data, from the selected particular activity solver,for the activity being performed in the received image in accordancewith the data indicating the activity state provided to the particularactivity solver; and providing, for display, a representation of thesolution data, obtained from the selected particular activity solver,for the activity being performed in the received image.
 2. The method ofclaim 1, wherein generating a rectified image of the surface comprises:identifying a first perspective associated with the surface in thereceived image; determining a second perspective associated with therectified image of the surface, wherein the first perspective isdifferent from the second perspective; and generating the rectifiedimage of the surface using the second perspective.
 3. The method ofclaim 1, wherein determining an activity being performed in the receivedimage, the activity being configured to be performed on a surface,comprises identifying the surface using quadrilateral rectification. 4.The method of claim 1, wherein determining an activity state of theactivity being performed in the received image based on the rectifiedimage and the configuration data comprises: dividing the rectified imageinto a plurality of image regions; for each respective image region ofthe plurality of image regions, determining state data associated withthe respective image region; and determining the activity state of theactivity being performed in the received image based on the state dataassociated with the plurality of image regions.
 5. The method of claim1, comprising: detecting a relative arrangement of features within thereceived image based on one or more training images associated with theactivity; and determining a mapping between the received image and therectified image.
 6. The method of claim 1, wherein determining anactivity state of the activity being performed in the received imagecomprises determining the activity state using optical characterrecognition.
 7. The method of claim 1, wherein determining an activitystate of the activity being performed in the received image comprisesmatching a portion of the received image with one or more trainingimages associated with the activity.
 8. A non-transitorycomputer-readable medium storing instructions, which, when executed byone or more computers, cause the one or more computers to performoperations of: receiving an image; determining an activity beingperformed in the received image, wherein the activity is configured tobe performed on a surface; selecting (i) a particular activity solver,from a set of activity solvers stored in memory, that provides solutiondata for the activity being performed in the received image and (ii)configuration data associated with the activity being performed in thereceived image; based on the configuration data associated with theactivity being performed in the received image, (i) generating arectified image of the surface of the activity performed in the receivedimage, and (ii) determining an activity state of the activity beingperformed in the received image; wherein determining an activity stateof the activity being performed in the received image is based on therectified image in addition to the configuration data associated withthe activity being performed in the received image; providing dataindicating the activity state to the particular activity solver,selected from the set of activity solvers, that provides solution datafor the activity being performed in the received image; in response toproviding data indicating the activity state to the particular activitysolver, obtaining solution data, from the selected particular activitysolver, for the activity being performed in the received image inaccordance with the data indicating the activity state provided to theparticular activity solver; and providing, for display, a representationof the solution data, obtained from the selected particular activitysolver, for the activity being performed in the received image.
 9. Thecomputer-readable medium of claim 8, wherein generating a rectifiedimage of the surface comprises: identifying a first perspectiveassociated with the surface in the received image; determining a secondperspective associated with the rectified image of the surface, whereinthe first perspective is different from the second perspective; andgenerating the rectified image of the surface using the secondperspective.
 10. The computer-readable medium of claim 8, whereindetermining an activity being performed in the received image, theactivity being configured to be performed on a surface, comprisesidentifying the surface using quadrilateral rectification.
 11. Thecomputer-readable medium of claim 8, wherein determining an activitystate of the activity being performed in the received image based on therectified image and the configuration data comprises: dividing therectified image into a plurality of image regions; for each respectiveimage region of the plurality of image regions, determining state dataassociated with the respective image region; and determining theactivity state of the activity being performed in the received imagebased on the state data associated with the plurality of image regions.12. The computer-readable medium of claim 8, the operations furthercomprising: detecting a relative arrangement of features within thereceived image based on one or more training images associated with theactivity; and determining a mapping between the received image and therectified image.
 13. The computer-readable medium of claim 8, whereindetermining an activity state of the activity being performed in thereceived image comprises determining the activity state using opticalcharacter recognition.
 14. The computer-readable medium of claim 8,wherein determining an activity state of the activity being performed inthe received image comprises matching a portion of the received imagewith one or more training images associated with the activity.
 15. Asystem comprising: one or more processors and one or more computerstorage media storing instructions that are operable, when executed bythe one or more processors, to cause the one or more processors toperform operations comprising: receiving an image; determining anactivity being performed in the received image, wherein the activity isconfigured to be performed on a surface; selecting (i) a particularactivity solver, from a set of activity solvers stored in memory, thatprovides solution data for the activity being performed in the receivedimage and (ii) configuration data associated with the activity beingperformed in the received image; based on the configuration dataassociated with the activity being performed in the received image, (i)generating a rectified image of the surface of the activity performed inthe received image, and (ii) determining an activity state of theactivity being performed in the received image; wherein determining anactivity state of the activity being performed in the received image isbased on the rectified image in addition to the configuration dataassociated with the activity being performed in the received image;providing data indicating the activity state to the particular activitysolver, selected from the set of activity solvers, that providessolution data for the activity being performed in the received image; inresponse to providing data indicating the activity state to theparticular activity solver, obtaining solution data, from the selectedparticular activity solver, for the activity being performed in thereceived image in accordance with the data indicating the activity stateprovided to the particular activity solver; and providing, for display,a representation of the solution data, obtained from the selectedparticular activity solver, for the activity being performed in thereceived image.
 16. The system of claim 15, wherein generating arectified image of the surface comprises: identifying a firstperspective associated with the surface in the received image;determining a second perspective associated with the rectified image ofthe surface, wherein the first perspective is different from the secondperspective; and generating the rectified image of the surface using thesecond perspective.
 17. The system of claim 15, wherein determining anactivity being performed in the received image, the activity beingconfigured to be performed on a surface, comprises identifying thesurface using quadrilateral rectification.
 18. The system of claim 15,wherein determining an activity state of the activity being performed inthe received image based on the rectified image and the configurationdata comprises: dividing the rectified image into a plurality of imageregions; for each respective image region of the plurality of imageregions, determining state data associated with the respective imageregion; and determining the activity state of the activity beingperformed in the received image based on the state data associated withthe plurality of image regions.
 19. The system of claim 15, theoperations further comprising: detecting a relative arrangement offeatures within the received image based on one or more training imagesassociated with the activity; and determining a mapping between thereceived image and the rectified image.
 20. The system of claim 15,wherein determining an activity state of the activity being performed inthe received image comprises at least one of: (i) determining theactivity state using optical character recognition, and (ii) matching aportion of the received image with one or more training imagesassociated with the activity.